Object Detection using the ImageAI Library in Python


  • Renas Rajab Asaad Department of Computer Science, Nawroz University, Duhok, KRG -Iraq
  • Rasan Ismael Ali Researcher
  • Awaz Ahmad Shaban Researcher
  • Merdin Shamal Salih Researcher




Python, OpenCV, Computer Vision, Image Processing


Recent progress in deep learning methods has shown that key steps in object detection and recognition, including feature extraction, region proposals, and classification, can be done using ImageAi libraries. Object detection is a computer vision technique that works to identify and locate objects within an image or video. Specifically, object detection draws bounding boxes around these detected objects, which allow us to locate where said objects are in a given scene. Object detection is commonly confused with image recognition, so before we proceed, it’s important that we clarify the distinctions between them. In that it aids in our comprehension and analysis of scenes in images or videos, object detection is intrinsically tied to other related computer vision techniques like image recognition and image segmentation. Significant variations. Image segmentation develops a pixel-level comprehension of a scene's elements while image recognition just produces a class label for an identified object. Object detection differs from these other jobs in that it has the capacity to specifically find objects inside an image or video. This enables us to count such things and later track them.


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How to Cite

Rajab Asaad, R., Ismael Ali, R., Ahmad Shaban, A., & Shamal Salih, M. (2023). Object Detection using the ImageAI Library in Python. Polaris Global Journal of Scholarly Research and Trends, 2(2), 1–9. https://doi.org/10.58429/pgjsrt.v2n2a143




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